Root-o-Mat: A novel tool for 2D image processing of root-soil interactions and its application in soil zymography

We developed a software tool enabling user-friendly and standardized pre- and post-processing of images of rooted soil by combining image processing techniques such as image registration, calibration, and segmentation in a graphical user interface. The added benefits of this image processing approach include an improved workflow in soil zymography. For evaluation, we conducted a rhizobox experiment with maize and determined the activity of leucine-aminopeptidase before and after glucose addition based on soil zymography. The temporal and spatial distribution of enzyme activity at the root-soil interface can be visualized by Root-o-Mat which offers 1) standardized image pre-processing, 2) calibration, 3) identification of hotspots of various intensity thresholds, 4) spatial analysis for selected roots, 5) inter-active illustration of enzyme activity profile lines, 6) image viewer, and 7) detection of temporal changes of enzyme activity. Registering images of the same rhizobox taken in successive periods allows further temporal and spatial analysis. We conclude that Root-o-Mat simplifies and firmly anchors image processing and image analyses in soil zymography. The new software can be downloaded for free (www.root-o-mat.de). © 2021 Elsevier Ltd

Авторы
Tegtmeier J.1, 2 , Dippold M.A.2 , Kuzyakov Y. 3, 4, 5 , Spielvogel S.1 , Loeppmann S.1, 2
Издательство
Elsevier Ltd
Язык
Английский
Статус
Опубликовано
Номер
108236
Том
157
Год
2021
Организации
  • 1 Institute of Plant Nutrition and Soil Science, Christian-Albrechts-University, Kiel, Germany
  • 2 Biogeochemistry of Agroecosystems, Department of Crop Sciences, Georg-August-University, Göttingen, Germany
  • 3 Dept. of Agricultural Soil Science, Georg-August-University, Göttingen, Germany
  • 4 Dept. of Soil Science of Temperate Ecosystems, Georg-August-University, Göttingen, Germany
  • 5 Agro-Technological Institute, RUDN University, Moscow
  • 6 Institute of Environmental Sciences, Kazan Federal University, Kazan, Russian Federation
Ключевые слова
2D image processing; Hotspot identification; Image referencing tool; Image registration; Rhizosphere spatiotemporal organization; Visualization approaches
Дата создания
20.04.2021
Дата изменения
20.04.2021
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/71966/
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